Life‐history traits of a tropical bagrid catfish, Mystus mysticetus Roberts, 1992, caught from the Mekong Delta, Vietnam

Abstract Population's biological parameters, including length at first capture, mortalities, exploitation rates, growth coefficient, longevity, and recruitment times, are essential in assessing fishing status, but there is no data on Mystus mysticetus. Therefore, the study was conducted to provide these parameters to assess the fishing status of this species at Cai Rang, Can Tho (CRCT) and Long Phu, Soc Trang (LPST). A collection of 741 individual fish was used for analysis and showed that most fish size groups ranged from 9.0 cm to 12.0 cm, and the asymptotic length was 16.8 cm for both CRCT and LPST populations. The fish population von Bertalanffy curve was L t = 16.80(1 − e−0.51(t + 0.38)) at CRCT and L t = 16.80(1 − e−0.48(t + 0.40)) at LPST. The fish growth coefficient at CRCT (2.16) was higher than at LPST (2.13), whereas the reverse case was true for longevity ranging from 5.88 years (at CRCT) to 6.25 years (at LPST). At CRCT, fishing mortality, natural mortality, total mortality, and exploitation rate were 0.69/year, 1.40/year, 2.09/year, and 0.33, respectively; at LPST, these values were 0.75/year, 1.33/year, 2.08/year, and 0.36, respectively. Although the population parameter of this fish species exhibited a spatial variation, both CRCT and LPST fish resources have not been subjected to overexploit because E (0.33 at CRCT and 0.36 at LPST) is lower than E 0.1 (0.707 at CRCT and 0.616 at LPST).

albolineatus (Robert, 1994) (Tran et al., 2013). They live at the bottom of freshwater bodies, migrating into flooded forests during the wet season and returning to the river's lower reaches in November and December of the lunar calendar (Rainboth, 1996;Vo et al., 2023).
That migration feature has created a difference in the habitat of M. mysticetus and may lead to the ability to change morphology to adapt to different habitats (Nguyen & Duong, 2020;Vo et al., 2021).
Mystus mysticetus is one of the target-catching catfish and plays a vital role in the local food supply .
Aquatic resources are essential to the lives of communities worldwide, and one of the crucial tasks of studying population variability is estimating the population's parameters, such as abundance, growth, recruitment period, mortalities, length at first capture, longevity, and exploitation rate (Tran, 2010). These parameters are used to assess the fishing status of the fish population (Amezcua et al., 2006), but the data on M. mysticetus populations along the Hau River, where they are fishing for food provision, is limited.
Cai Rang, Can Tho (CRCT) has favorable climatic and hydrological conditions with fresh water all year round, whereas the Long Phu, Soc Trang (LPST) is affected by saline intrusion in the dry season (Nguyen et al., 2021). This phenomenon regulates the variation in population biological parameters of fish, for example, Glossogobius sparsipapillus exhibits significant differences in growth performance; longevity; total, natural, and fishing mortalities between CRCT and LPST (Nguyen et al., 2021). Therefore, this study aimed to provide parameters such as first catch length, longevity, growth coefficient, exploitation rate, mortalities, and recruitment time of this species and verify if these parameters in CRCT and LPST exhibit a variation.
These parameters are the basis for fish ecological adaptation and fishing assessment to set up a reasonable exploitation strategy for this fish resource in CRCT and LPST.

| Sampling site and fish collection
The study was carried out at two sites along the Hau River: CRCT, which is freshwater, and LPST, which is brackish water (Figure 1) because M. mysticetus displayed a wide distribution from freshwater to salted water. Each month, M. mysticetus samples were collected using trawl nets with a size length of 15 m, height of 3 m, and codeend mesh of 2a = 1.5 cm from January 2022 to December 2022 with ~30 fish samples/month. Each sampling period lasted 2 days, and nets were set up during high tide and retrieved during low tide at each sampling site, where the pH, temperature, and salinity were also measured using the HI98107 tool (pH and temperature) and a refractometer 950.0100 PPT-ATC (salinity). The fish samples, after collection, were identified based on the morphological characteristics described by Tran et al. (2013) and transported to the Laboratory for further analysis. Fish samples were measured in total length (L, cm) to determine the length frequency.

| Data analysis
The population biological parameters were determined through length frequency data of males and females at two sites. Male and female data were combined at each location to ensure an adequate sample size. The procedure was performed as described by Amarasinghe and De Silva (1992) to minimize length-frequency bias due to gear selection's effect. The Powell-Wetherall approach was applied to estimate the initial L ∞ via the linear regression: L m − L' = a + bL (L': the cut-off length; L m : the mean length of all fish; b: the slope; a: the intercept; L ∞ = a/b) (Wetherall, 1986). Next, the ELEFAN I procedure was performed to determine the initial growth parameter (K) from the fish's initial L ∞ and length frequency (Gayanilo et al., 2005).
The growth coefficient (Φ') was estimated from the formula suggested by Pauly and Munro (1984): Φ2 = logK + 2logL ∞ . This coefficient was species-specific and is used to compare the Φ' of the same species but distributed in different regions or between species within a genus or subfamily or a family with the same distribution based on the research method proposed by Tran et al. (2007).
The longevity (t max ) was determined as t max = 3/K (Pauly, 1980;Taylor, 1958). The yield curve converted routine was applied to determine the total mortality (Z) (Pauly et al., 1995). The natural mortality (M) was determined by the formula of Pauly (1980): According to Ricker (1975), fishing mortality (F)-the number of individual fish that die directly or indirectly due to fishing activity-was calculated as F = Z-M; and the exploitation rate (E) was determined The length at which 50% of the fish were caught was called the first catch length (L c ) and was determined by the yield curve transformation equation (Pauly, 1987). The yield/recruitment (Y′/R) and biomass/recruitment (B′/R) models of Beverton and Holt (1957) were used to estimate the maximum exploitation coefficient (E max ), optimal mining factor (E 10 ), and mining factor at which B′/R was reduced by 50% (E 50 ). Based on the research method of Pauly and Soriano (1986), the combination of isopleth (L c /L ∞ ) and exploitation rate (E) was used to determine the fishing status of the fish.
The above population biological parameters were obtained by performing FiSAT II software. The temperature, pH, and salinity variation between the dry and wet seasons and sampling sites were quantified using one-way ANOVA performed by SPSS v.21 at a significance level of 5% (please find the result in the Appendix S1).

| RE SULTS
The length frequency data of this fish were determined based on the

| DISCUSS ION
The Φ' of the CRCT population (2.158) was higher than that of the LPST population (2.132) could be due to differences in maximum length between these species. This variation could be related to the variation of temperature, pH, and salinity between these two sites, which was found in Pauly and Munro (1984), who indicated that environmental factors could affect the fish growth coefficient  (Ragheb, 2014).
Although located in the Mekong Delta, in each ecological region, fish had different growth rates . in Egypt (Ragheb, 2014). The cause of this difference could have been the difference in economic value and the diversity of fishing gear.
At CRCT and LPST, the E of M. mysticetus was lower than E 10 , suggesting that the fish stocks in these regions were not subjected to overexploited. The fish age at LPST tended to be caught earlier than at CRCT, as L c /L ∞ at LPST (0.535) was lower than at CRCT (0.620). Likewise, studies on several species of Bagridae shared similar results, for example, M. gulio in Bangladesh (Mustafa et al., 2019) and C. auratus in Egypt (Ragheb, 2014). On the other hand, some populations of Bagridae are overexploited, such as C. nigrodigitatus in Côte d'Ivoire (Bédia et al., 2017) and C. nigrodigitatus in Ghana (Ofori-Danson et al., 2002).
The variations in temperature, pH, and salinity at CRCT and LPST seem to cause significant differences in population biological parameters in this fish. In which, the salinity could be the most substantial influencing factor for parameters such as longer longevity at LPST and higher growth coefficient at CRCT. However, some morphological parameters showed stability with the environment of this fish as the maximum length remains unchanged, and the exploitation rate was similar. With harsher conditions at LPST, the natural mortality in this area (0.75/year) was significantly higher than that at CRCT (0.69/year). Sudden changes in salinity conditions could lead to fish at increased mortality risk or poorer vitality. The difference in these two regions affected not only the population of this fish but also many other fish species in the same distribution area. In the Gobiidae family, G. sparsipapillus showed this difference (Nguyen et al., 2021). Specifically, in this fish, there was a difference in the sex ratio at CRCT (females and males were equal in number) and LPST (males predominate in number). The t max at CRCT displayed a higher value than that of LPST, but the opposite result was found in Φ'. Like M. mysticetus, G. sparsipapillus had an equivalent maximum length between these two regions. Some other fish species also displayed a variation in population parameters regarding ecological regions, for example, Periophthalmus chrysospilos exhibited a better adaptation to areas with low salinity (Ben Tre and Tra Vinh) than to areas with higher salinity (Soc Trang and Bac Lieu) . Meanwhile, Acentrogobius viridipunctatus displayed a higher growth coefficient in the high salinity areas (Bac Lieu and Ca Mau) . That showed environmental conditions in different environments could affect some fish population parameters. Conceptualization (equal); funding acquisition (equal); investigation (equal); methodology (equal); resources (equal); validation (equal);

ACK N OWLED G M ENTS
We are grateful to the local fishers for their help in fish collection.
We also would like to thank the anonymous reviewers and editors for their very useful comments that significantly improved the earlier version of this manuscript.

FU N D I N G I N FO R M ATI O N
This work is supported by Can Tho University under grant number TSV2022-137.

CO N FLI C T O F I NTE R E S T S TATE M E NT
The authors declare that they have no competing interests.

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